Automated Security Analysis

Security Checks for
AI Applications

Airbolt analyzes your AI-powered application for exposed credentials, unsafe model flows, prompt injection risks, and known vulnerabilities — before you launch.

40+
Credential Patterns
6
Security Engines
<5min
Full Scan Time

AI-assisted code ships fast.
Security review often doesn't.

Modern AI coding tools accelerate development significantly. But speed without review creates exposure. These are the most common gaps we find.

Exposed API keys leak real costs

Hardcoded OpenAI and Anthropic credentials in source code, committed .env files, and tokens bundled into client-side assets result in unauthorized usage and unexpected bills.

Prompt injection channels compromise data

User input passed directly to model calls without validation creates attack surfaces. System prompts, internal data, and application logic become extractable.

Unprotected endpoints increase attack surface

RAG query routes without authentication, model call endpoints without rate limiting, and misconfigured session handling expose your application to abuse.

Focused analysis for
AI application security.

Airbolt runs targeted checks across the areas where AI-generated code most commonly introduces vulnerabilities.

Credential and secret exposure

Detection of hardcoded API keys, tokens, and secrets across 40+ AI service providers including OpenAI, Anthropic, Pinecone, and cloud platforms.

Unsafe model request patterns

Identification of direct user input to model calls, exposed system prompts, and prompt injection surfaces in your LLM integration code.

Unvalidated input paths

Analysis of request handlers where user-supplied data reaches model APIs, vector stores, or tool execution flows without sanitization.

Dependency vulnerabilities

Automated audit of npm and pip packages against known CVE databases. Identification of outdated or compromised dependencies in your stack.

Upload. Scan. Review.

No integrations required. No agents running on your infrastructure. Upload a ZIP archive and receive a structured report.

01

Upload your project

ZIP your codebase and upload it securely. Any stack — Next.js, Python, Node, Rails, or other frameworks.

30 seconds
02

Automated analysis

Secrets detection, dependency audit, static analysis rules, and AI-specific heuristics run against your code.

~2 minutes
03

Structured report

Categorized findings by severity. Summary of priority items. Downloadable PDF with the Full AI Scan.

Instant

What your report looks like.

Each scan produces a structured, categorized security report. Here's an example of what you'll receive.

airbolt-report-2026-02-21.pdf
Security Analysis — my-ai-saas
Scanned 247 files · 6 engines · Feb 21, 2026
MEDIUM
Risk Level
CRIT OpenAI API key hardcoded in /lib/ai-client.ts:14
HIGH Prompt injection — req.body.prompt passed to chat completion without validation
HIGH System prompt exposed in /api/chat response headers
MED 3 dependencies with known vulnerabilities (CVE-2025-xxxx)

Less than a coffee a day.
More than an enterprise audit.

One-time scans. No subscriptions. No contracts. Pay only when you ship.

Lite Scan

€9 / scan

Quick security sanity check

  • Secrets detection
  • Dependency vulnerability scan
  • Risk score
  • Web-based report
  • No AI analysis
  • No PDF export

Common questions.

Airbolt runs secrets detection, dependency vulnerability audits, static analysis, and AI-specific heuristics against your codebase. This includes checks for hardcoded API keys, prompt injection surfaces, exposed system prompts, unprotected endpoints, and known CVEs in your dependencies.

Most scans complete in under 5 minutes. The time depends on codebase size, but typical AI applications with fewer than 500 files complete in 1-2 minutes.

No. Your uploaded code is processed in an isolated environment and deleted immediately after the scan completes. We do not retain source code. Only the generated report is stored for your access.

Currently, Airbolt accepts ZIP uploads only. You can export any private repository as a ZIP and upload it directly. GitHub integration for direct repository access is planned for a future release.

AI applications introduce security risks that standard scanners don't cover — prompt injection, exposed model credentials, unprotected RAG endpoints, and unsafe tool execution flows. Airbolt includes heuristics specifically designed for these patterns.

Review your code
before deployment.

Join the waitlist to be notified when Airbolt is available for your first security scan.